IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding

CP204L Is a Multifunctional Protein of African Swine Fever Virus That Interacts with the VPS39 Subunit of the Homotypic Fusion and Vacuole Protein Sorting Complex and Promotes Lysosome Clustering

Virus replication depends on a complex interplay between viral and host proteins. In the case of African swine fever virus (ASFV), a large DNA virus, only a few virus-host protein-protein interactions have been identified to date. In this study, we demonstrate that the ASFV protein CP204L interacts with the cellular homotypic fusion and protein sorting (HOPS) protein VPS39, blocking its association with the lysosomal HOPS complex, which modulates endolysosomal trafficking and promotes lysosome clustering. Instead, CP204L and VPS39 are targeted to virus factories and localized at the periphery of the virus DNA replication sites. Furthermore, we show that loss of VPS39 reduces the levels of virus proteins synthesized in the early phase of infection and delays ASFV replication but does not completely inhibit it. Collectively, these results identify a novel virus-host protein interaction that modulates host membrane rearrangement during infection and provide evidence that CP204L is a multifunctional protein engaged in distinct steps of the ASFV life cycle. IMPORTANCE African swine fever virus (ASFV) was first identified over a hundred years ago. Since then, much effort has been made to understand the pathogenesis of ASFV. However, the specific roles of many individual ASFV proteins during the infection remain enigmatic. This study provides evidence that CP204L, one of the most abundant ASFV proteins, modulates endosomal trafficking during virus infection. Through protein-protein interaction, CP204L prevents the recruitment of VPS39 to the endosomal and lysosomal membranes, resulting in their accumulation. Consequently, CP204L and VPS39 become sequestered in the ASFV replication and assembly site, known as the virus factory. These results uncover a novel function of viral protein CP204L and extend our understanding of complex interaction between virus and host.

Structural Analysis of Genomic and Proteomic Signatures Reveal Dynamic Expression of Intrinsically Disordered Regions in Breast Cancer and Tissue

Structural features of proteins capture underlying information about protein evolution and function, which enhances the analysis of proteomic and transcriptomic data. Here we develop Structural Analysis of Gene and protein Expression Signatures (SAGES), a method that describes expression data using features calculated from sequence-based prediction methods and 3D structural models. We used SAGES, along with machine learning, to characterize tissues from healthy individuals and those with breast cancer. We analyzed gene expression data from 23 breast cancer patients and genetic mutation data from the COSMIC database as well as 17 breast tumor protein expression profiles. We identified prominent expression of intrinsically disordered regions in breast cancer proteins as well as relationships between drug perturbation signatures and breast cancer disease signatures. Our results suggest that SAGES is generally applicable to describe diverse biological phenomena including disease states and drug effects.

Non-synonymous variation and protein structure of candidate genes associated with selection in farm and wild populations of turbot (Scophthalmus maximus)

Non-synonymous variation (NSV) of protein coding genes represents raw material for selection to improve adaptation to the diverse environmental scenarios in wild and livestock populations. Many aquatic species face variations in temperature, salinity and biological factors throughout their distribution range that is reflected by the presence of allelic clines or local adaptation. The turbot (Scophthalmus maximus) is a flatfish of great commercial value with a flourishing aquaculture which has promoted the development of genomic resources. In this study, we developed the first atlas of NSVs in the turbot genome by resequencing 10 individuals from Northeast Atlantic Ocean. More than 50,000 NSVs where detected in the ~ 21,500 coding genes of the turbot genome, and we selected 18 NSVs to be genotyped using a single Mass ARRAY multiplex on 13 wild populations and three turbot farms. We detected signals of divergent selection on several genes related to growth, circadian rhythms, osmoregulation and oxygen binding in the different scenarios evaluated. Furthermore, we explored the impact of NSVs identified on the 3D structure and functional relationship of the correspondent proteins. In summary, our study provides a strategy to identify NSVs in species with consistently annotated and assembled genomes to ascertain their role in adaptation.

Molecular Mechanisms of MmpL3 Function and Inhibition

Mycobacteria species include a large number of pathogenic organisms such as Mycobacterium tuberculosis, Mycobacterium leprae, and various non-tuberculous mycobacteria. Mycobacterial membrane protein large 3 (MmpL3) is an essential mycolic acid and lipid transporter required for growth and cell viability. In the last decade, numerous studies have characterized MmpL3 with respect to protein function, localization, regulation, and substrate/inhibitor interactions. This review summarizes new findings in the field and seeks to assess future areas of research in our rapidly expanding understanding of MmpL3 as a drug target. An atlas of known MmpL3 mutations that provide resistance to inhibitors is presented, which maps amino acid substitutions to specific structural domains of MmpL3. In addition, chemical features of distinct classes of Mmpl3 inhibitors are compared to provide insights into shared and unique features of varied MmpL3 inhibitors.

Ocular protein optineurin shows reversibility from unfolded states and exhibits chaperone-like activity

Optineurin (OPTN) is a multifunctional, ubiquitously expressed cytoplasmic protein, mutants of which are associated with primary open-angle glaucoma (POAG) and amyotrophic lateral sclerosis (ALS). The most abundant heat shock protein crystallin, known for its remarkable thermodynamic stability and chaperoning activity, allows ocular tissues to withstand stress. The presence of OPTN in ocular tissues is intriguing. Interestingly, OPTN also harbors heat shock elements in its promoter region. Sequence analysis of OPTN exhibits intrinsically disordered regions and nucleic acid binding domains. These properties hinted that OPTN might be endowed with sufficient thermodynamic stability and chaperoning activity. However, these attributes of OPTN have not yet been explored. Here, we studied these properties through thermal and chemical denaturation experiments and monitored the processes using CD, fluorimetry, differential scanning calorimetry, and dynamic light scattering. We found that upon heating, OPTN reversibly forms higher-order multimers. OPTN also displayed a chaperone-like function by reducing the thermal aggregation of bovine carbonic anhydrase. It regains its native secondary structure, RNA-binding property, and melting temperature (T _m) after refolding from a thermally as well as chemically denatured state. From our data, we conclude that OPTN, with its unique ability to revert from the stress-mediated unfolded state and its unique chaperoning function, is a valuable protein of the ocular tissues.

Structural organization of RDGB (retinal degeneration B), a multi-domain lipid transfer protein: a molecular modelling and simulation based approach

Lipid transfer proteins (LTPs) that shuttle lipids at membrane contact sites (MCS) play an important role in maintaining cellular homeostasis. One such important LTP is the Retinal Degeneration B (RDGB) protein. RDGB is localized at the MCS formed between the endoplasmic reticulum (ER) and the apical plasma membrane (PM) in Drosophila photoreceptors where it transfers phosphatidylinositol (PI) during G-protein coupled phospholipase C signalling. Previously, the C-terminal domains of RDGB have been shown to be essential for its function and accurate localization. In this study, using in-silico integrative modelling we predict the structure of entire RDGB protein in complex with the ER membrane protein VAP. The structure of RDGB has then been used to decipher the structural features of the protein important for its orientation at the contact site. Using this structure, we identify two lysine residues in the C-terminal helix of the LNS2 domain important for interaction with the PM. Using molecular docking, we also identify an unstructured region USR1, immediately c-terminal to the PITP domain that is important for the interaction of RDGB with VAP. Overall the 10.06 nm length of the predicted RDGB-VAP complex spans the distance between the PM and ER and is consistent with the cytoplasmic gap between the ER and PM measured by transmission electron microscopy in photoreceptors. Overall our model explains the topology of the RDGB-VAP complex at this ER-PM contact site and paves the way for analysis of lipid transfer function in this setting.Communicated by Ramaswamy H. Sarma.

A Fijivirus Major Viroplasm Protein Shows RNA-Stimulated ATPase Activity by Adopting Pentameric and Hexameric Assemblies of Dimers

Fijiviruses replicate and package their genomes within viroplasms in a process involving RNA-RNA and RNA-protein interactions. Here, we demonstrate that the 24 C-terminal residues (C-arm) of the P9-1 major viroplasm protein of the mal de Río Cuarto virus (MRCV) are required for its multimerization and the formation of viroplasm-like structures. Using an integrative structural approach, the C-arm was found to be dispensable for P9-1 dimer assembly but essential for the formation of pentamers and hexamers of dimers (decamers and dodecamers), which favored RNA binding. Although both P9-1 and P9-1ΔC-arm catalyzed ATP with similar activities, an RNA-stimulated ATPase activity was only detected in the full-length protein, indicating a C-arm-mediated interaction between the ATP catalytic site and the allosteric RNA binding sites in the (do)decameric assemblies. A stronger preference to bind phosphate moieties in the decamer was predicted, suggesting that the allosteric modulation of ATPase activity by RNA is favored in this structural conformation. Our work reveals the structural versatility of a fijivirus major viroplasm protein and provides clues to its mechanism of action. IMPORTANCE The mal de Río Cuarto virus (MRCV) causes an important maize disease in Argentina. MRCV replicates in several species of Gramineae plants and planthopper vectors. The viral factories, also called viroplasms, have been studied in detail in animal reovirids. This work reveals that a major viroplasm protein of MRCV forms previously unidentified structural arrangements and provides evidence that it may simultaneously adopt two distinct quaternary assemblies. Furthermore, our work uncovers an allosteric communication between the ATP and RNA binding sites that is favored in the multimeric arrangements. Our results contribute to the understanding of plant reovirids viroplasm structure and function and pave the way for the design of antiviral strategies for disease control.

VGLL3 is a mechanosensitive protein that promotes cardiac fibrosis through liquid-liquid phase separation

Myofibroblasts cause tissue fibrosis by producing extracellular matrix proteins, such as collagens. Humoral factors like TGF-β, and matrix stiffness are important for collagen production by myofibroblasts. However, the molecular mechanisms regulating their ability to produce collagen remain poorly characterised. Here, we show that vestigial-like family member 3 (VGLL3) is specifically expressed in myofibroblasts from mouse and human fibrotic hearts and promotes collagen production. Further, substrate stiffness triggers VGLL3 translocation into the nucleus through the integrin β1-Rho-actin pathway. In the nucleus, VGLL3 undergoes liquid-liquid phase separation via its low-complexity domain and is incorporated into non-paraspeckle NONO condensates containing EWS RNA-binding protein 1 (EWSR1). VGLL3 binds EWSR1 and suppresses miR-29b, which targets collagen mRNA. Consistently, cardiac fibrosis after myocardial infarction is significantly attenuated in Vgll3-deficient mice, with increased miR-29b expression. Overall, our results reveal an unrecognised VGLL3-mediated pathway that controls myofibroblasts' collagen production, representing a novel therapeutic target for tissue fibrosis.

Computational Prediction of Protein Intrinsically Disordered Region Related Interactions and Functions

Intrinsically Disordered Proteins (IDPs) and Regions (IDRs) exist widely. Although without well-defined structures, they participate in many important biological processes. In addition, they are also widely related to human diseases and have become potential targets in drug discovery. However, there is a big gap between the experimental annotations related to IDPs/IDRs and their actual number. In recent decades, the computational methods related to IDPs/IDRs have been developed vigorously, including predicting IDPs/IDRs, the binding modes of IDPs/IDRs, the binding sites of IDPs/IDRs, and the molecular functions of IDPs/IDRs according to different tasks. In view of the correlation between these predictors, we have reviewed these prediction methods uniformly for the first time, summarized their computational methods and predictive performance, and discussed some problems and perspectives.

Aggregation of Disordered Proteins Associated with Neurodegeneration

Cellular deposition of protein aggregates, one of the hallmarks of neurodegeneration, disrupts cellular functions and leads to neuronal death. Mutations, posttranslational modifications, and truncations are common molecular underpinnings in the formation of aberrant protein conformations that seed aggregation. The major proteins involved in neurodegeneration include amyloid beta (Aβ) and tau in Alzheimer's disease, α-synuclein in Parkinson's disease, and TAR DNA-binding protein (TDP-43) in amyotrophic lateral sclerosis (ALS). These proteins are described as intrinsically disordered and possess enhanced ability to partition into biomolecular condensates. In this review, we discuss the role of protein misfolding and aggregation in neurodegenerative diseases, specifically highlighting implications of changes to the primary/secondary (mutations, posttranslational modifications, and truncations) and the quaternary/supramolecular (oligomerization and condensation) structural landscapes for the four aforementioned proteins. Understanding these aggregation mechanisms provides insights into neurodegenerative diseases and their common underlying molecular pathology.

Novel insights into construct toxicity, strain optimization, and primary sequence design for producing recombinant silk fibroin and elastin-like peptide in E. coli

Spider silk proteins (spidroins) are a remarkable class of biomaterials that exhibit a unique combination of high-value attributes and can be processed into numerous morphologies for targeted applications in diverse fields. Recombinant production of spidroins represents the most promising route towards establishing the industrial production of the material, however, recombinant spider silk production suffers from fundamental difficulties that includes low titers, plasmid instability, and translational inefficiencies. In this work, we sought to gain a deeper understanding of upstream bottlenecks that exist in the field through the production of a panel of systematically varied spidroin sequences in multiple E. coli strains. A restriction on basal expression and specific genetic mutations related to stress responses were identified as primary factors that facilitated higher titers of the recombinant silk constructs. Using these findings, a novel strain of E. coli was created that produces recombinant silk constructs at levels 4-33 times higher than standard BL21(DE3). However, these findings did not extend to a similar recombinant protein, an elastin-like peptide. It was found that the recombinant silk proteins, but not the elastin-like peptide, exert toxicity on the E. coli host system, possibly through their high degree of intrinsic disorder. Along with strain engineering, a bioprocess design that utilizes longer culturing times and attenuated induction was found to raise recombinant silk titers by seven-fold and mitigate toxicity. Targeted alteration to the primary sequence of the recombinant silk constructs was also found to mitigate toxicity. These findings identify multiple points of focus for future work seeking to further optimize the recombinant production of silk proteins and is the first work to identify the intrinsic disorder and subsequent toxicity of certain spidroin constructs as a primary factor related to the difficulties of production.

Converting antimicrobial into targeting peptides reveals key features governing protein import into mitochondria and chloroplasts

We asked what peptide features govern targeting to the mitochondria versus the chloroplast, using antimicrobial peptides as a starting point. This approach was inspired by the endosymbiotic hypothesis that organelle-targeting peptides derive from antimicrobial amphipathic peptides delivered by the host cell, to which organelle progenitors became resistant. To explore the molecular changes required to convert antimicrobial into targeting peptides, we expressed a set of 13 antimicrobial peptides in Chlamydomonas reinhardtii. Peptides were systematically modified to test distinctive features of mitochondrion- and chloroplast-targeting peptides, and we assessed their targeting potential by following the intracellular localization and maturation of a Venus fluorescent reporter used as a cargo protein. Mitochondrial targeting can be achieved by some unmodified antimicrobial peptide sequences. Targeting to both organelles is improved by replacing lysines with arginines. Chloroplast targeting is enabled by the presence of flanking unstructured sequences, additional constraints consistent with chloroplast endosymbiosis having occurred in a cell that already contained mitochondria. If indeed targeting peptides evolved from antimicrobial peptides, then required modifications imply a temporal evolutionary scenario with an early exchange of cationic residues and a late acquisition of chloroplast-specific motifs.

Dissection of hubs and bottlenecks in a protein-protein interaction network

Analysis of degree centrality in conjunction with betweenness centrality of proteins in a human protein-protein interaction network revealed three categories of centrally important proteins: a) proteins with high degree and betweenness (hub-bottlenecks denoted as MX), b) proteins with high betweenness and low degree (non-hub-bottlenecks/pure bottlenecks denoted as PB) and c) proteins with high degree and low betweenness (hub-non-bottlenecks/pure hubs denoted as PH). When subjected to a detailed statistical analysis of their molecular-level properties, the proteins belonging to each of these categories were found to be associated with distinct canonical molecular properties, i.e., "molecular markers". The MX proteins are a) conformationally versatile, mainly comprising of essential proteins, b) the targets for interactions by the proteins of viral and bacterial pathogens, c) evolutionally constrained, involved in multiple pathways, enriched with disease genes and d) involved in the functions such as protein stabilization, phosphorylation, and mRNA slicing processes. PB proteins are a) enriched with extracellular and cancer-related proteins, b) enriched with the approved drug targets and c) involved in cell-cell signaling processes. Finally, PH are a) structurally versatile, b) enriched with essential proteins primarily involved in housekeeping processes (transcription and replication). The fact that the proteins belonging to these three categories form three distinct sets in terms of their molecular properties reveals the existence of trichotomy among hubs and bottlenecks, and this knowledge is of paramount importance while prioritizing protein targets for further studies such as drug design and disease association studies based on their network centrality values.

Human VH-based chimeric antigen receptor T cells targeting glypican 3 eliminate tumors in preclinical models of HCC

BACKGROUND AND AIMS

Efficacy of chimeric antigen receptor (CAR) T cells for treating solid tumors, including HCC, remains a challenge. Nanobodies are emerging building blocks of CAR T cells due to their small size and high expression. Membrane proximal sites have been shown as attractive epitopes of CAR T cells. However, current CAR formats are not tailored toward nanobodies or targeting membrane distal epitopes.

APPROACH AND RESULTS

Using hYP7 Fv (membrane proximal) and HN3 VH nanobody (membrane distal) as GPC3 targeting elements, we sought to determine how hinges and transmembrane portions of varying structures and sizes affect CAR T-cell function. We generated multiple permutations of CAR T cells containing CD8, CD28, IgG4, and Fc domains. We show that engineered HN3 CAR T cells can be improved by 2 independent, synergistic changes in the hinge and transmembrane domains. The T cells expressing the HN3 CAR which contains the hinge region of IgG4 and the CD28 transmembrane domain (HN3-IgG4H-CD28TM) exhibited high cytotoxic activity and caused complete HCC tumor eradication in immunodeficient mice. HN3-IgG4H-CD28TM CAR T cells were enriched for cytotoxic-memory CD8+ T cells and NFAT signals, and reduced β catenin levels in HCC cells.

CONCLUSION

Our findings indicate that altering the hinge and transmembrane domains of a nanobody-based CAR targeting a distal GPC3 epitope, in contrast to a membrane proximal epitope, lead to robust T-cell signaling and induce swift and durable eradication of HCC tumors.

In-solution structure and oligomerization of human histone deacetylase 6 - an integrative approach

Human histone deacetylase 6 (HDAC6) is a structurally unique, multidomain protein implicated in a variety of physiological processes including cytoskeletal remodelling and the maintenance of cellular homeostasis. Our current understanding of the HDAC6 structure is limited to isolated domains, and a holistic picture of the full-length protein structure, including possible domain interactions, is missing. Here, we used an integrative structural biology approach to build a solution model of HDAC6 by combining experimental data from several orthogonal biophysical techniques complemented by molecular modelling. We show that HDAC6 is best described as a mosaic of folded and intrinsically disordered domains that in-solution adopts an ensemble of conformations without any stable interactions between structured domains. Furthermore, HDAC6 forms dimers/higher oligomers in a concentration-dependent manner, and its oligomerization is mediated via the positively charged N-terminal microtubule-binding domain. Our findings provide the first insights into the structure of full-length human HDAC6 and can be used as a basis for further research into structure function and physiological studies of this unique deacetylase.

Nuclear-localized CTEN is a novel transcriptional regulator and promotes cancer cell migration through its downstream target CDC27

C-terminal tensin-like (CTEN) is a tensin family protein typically localized to the cytoplasmic side of focal adhesions, and primarily contributes to cell adhesion and migration. Elevated expression and nuclear accumulation of CTEN have been reported in several types of cancers and found to be associated with malignant behaviors. However, the function of nuclear CTEN remains elusive. In this study, we report for the first time that nuclear CTEN associates with chromatin DNA and occupies the region proximal to the transcription start site in several genes. The mRNA expression level of CTEN positively correlates with that of one of its putative target genes, cell division cycle protein 27 (CDC27), in a clinical colorectal cancer dataset, suggesting that CTEN may play a role in the regulation of CDC27 gene expression. Furthermore, we demonstrated that CTEN is recruited to the promoter region of the CDC27 gene and that the mRNA expression and promoter activity of CDC27 are both reduced when CTEN is downregulated. In addition, we found that enhanced nuclear accumulation of CTEN in HCT116 cells by overexpression of CTEN fused with nuclear localization signals increases CDC27 transcript levels and promoter activity. The increased nuclear-localized CTEN also significantly promotes cell migration, and the migratory ability is suppressed when CDC27 is knocked down. These results demonstrate that nuclear CTEN regulates CDC27 expression transcriptionally and promotes cell migration through CDC27. Our findings provide new insights into CTEN moonlighting in the nucleus as a DNA-associated protein and transcriptional regulator involved in modulating cancer cell migration.

Conformationally responsive dyes enable protein-adaptive differential scanning fluorimetry

Flexible in vitro methods alter the course of biological discoveries. Differential Scanning Fluorimetry (DSF) is a particularly versatile technique which reports protein thermal unfolding via fluorogenic dye. However, applications of DSF are limited by widespread protein incompatibilities with the available DSF dyes. Here, we enable DSF applications for 66 of 70 tested proteins (94%) including 10 from the SARS-CoV2 virus using a chemically diverse dye library, Aurora, to identify compatible dye-protein pairs in high throughput. We find that this protein-adaptive DSF platform (paDSF) not only triples the previous protein compatibility, but also fundamentally extends the processes observable by DSF, including interdomain allostery in O-GlcNAc Transferase (OGT). paDSF enables routine measurement of protein stability, dynamics, and ligand binding.

DNA binding and RAD51 engagement by the BRCA2 C-terminus orchestrate DNA repair and replication fork preservation

The tumor suppressor BRCA2 participates in DNA double-strand break repair by RAD51-dependent homologous recombination and protects stressed DNA replication forks from nucleolytic attack. We demonstrate that the C-terminal Recombinase Binding (CTRB) region of BRCA2, encoded by gene exon 27, harbors a DNA binding activity. CTRB alone stimulates the DNA strand exchange activity of RAD51 and permits the utilization of RPA-coated ssDNA by RAD51 for strand exchange. Moreover, CTRB functionally synergizes with the Oligonucleotide Binding fold containing DNA binding domain and BRC4 repeat of BRCA2 in RPA-RAD51 exchange on ssDNA. Importantly, we show that the DNA binding and RAD51 interaction attributes of the CTRB are crucial for homologous recombination and protection of replication forks against MRE11-mediated attrition. Our findings shed light on the role of the CTRB region in genome repair, reveal remarkable functional plasticity of BRCA2, and help explain why deletion of Brca2 exon 27 impacts upon embryonic lethality.

Plasmodium sporozoites require the protein B9 to invade hepatocytes

Plasmodium sporozoites are transmitted to a mammalian host during blood feeding by an infected mosquito and invade hepatocytes for initial replication of the parasite into thousands of erythrocyte-invasive merozoites. Here we report that the B9 protein, a member of the 6-cysteine domain protein family, is secreted from sporozoite micronemes and is required for productive invasion of hepatocytes. The N-terminus of B9 forms a beta-propeller domain structurally related to CyRPA, a cysteine-rich protein forming an essential invasion complex in Plasmodium falciparum merozoites. The beta-propeller domain of B9 is essential for sporozoite infectivity and interacts with the 6-cysteine proteins P36 and P52 in a heterologous expression system. Our results suggest that, despite using distinct sets of parasite and host entry factors, Plasmodium sporozoites and merozoites may share common structural modules to assemble protein complexes for invasion of host cells.

Liaisons dangereuses: Intrinsic Disorder in Cellular Proteins Recruited to Viral Infection-Related Biocondensates

Liquid-liquid phase separation (LLPS) is responsible for the formation of so-called membrane-less organelles (MLOs) that are essential for the spatio-temporal organization of the cell. Intrinsically disordered proteins (IDPs) or regions (IDRs), either alone or in conjunction with nucleic acids, are involved in the formation of these intracellular condensates. Notably, viruses exploit LLPS at their own benefit to form viral replication compartments. Beyond giving rise to biomolecular condensates, viral proteins are also known to partition into cellular MLOs, thus raising the question as to whether these cellular phase-separating proteins are drivers of LLPS or behave as clients/regulators. Here, we focus on a set of eukaryotic proteins that are either sequestered in viral factories or colocalize with viral proteins within cellular MLOs, with the primary goal of gathering organized, predicted, and experimental information on these proteins, which constitute promising targets for innovative antiviral strategies. Using various computational approaches, we thoroughly investigated their disorder content and inherent propensity to undergo LLPS, along with their biological functions and interactivity networks. Results show that these proteins are on average, though to varying degrees, enriched in disorder, with their propensity for phase separation being correlated, as expected, with their disorder content. A trend, which awaits further validation, tends to emerge whereby the most disordered proteins serve as drivers, while more ordered cellular proteins tend instead to be clients of viral factories. In light of their high disorder content and their annotated LLPS behavior, most proteins in our data set are drivers or co-drivers of molecular condensation, foreshadowing a key role of these cellular proteins in the scaffolding of viral infection-related MLOs.

Non-catalytic role of phosphoinositide 3-kinase in mesenchymal cell migration through non-canonical induction of p85β/AP-2-mediated endocytosis

Class IA phosphoinositide 3-kinase (PI3K) galvanizes fundamental cellular processes such as migration, proliferation, and differentiation. To enable multifaceted roles, the catalytic subunit p110 utilizes a multi-domain, regulatory subunit p85 through its inter SH2 domain (iSH2). In cell migration, their product PI(3,4,5)P3 generates locomotive activity. While non-catalytic roles are also implicated, underlying mechanisms and its relationship to PI(3,4,5)P3 signaling remain elusive. Here, we report that a disordered region of iSH2 contains previously uncharacterized AP-2 binding motifs which can trigger clathrin and dynamin-mediated endocytosis independent of PI3K catalytic activity. The AP-2 binding motif mutants of p85 aberrantly accumulate at focal adhesions and upregulate both velocity and persistency in fibroblast migration. We thus propose the dual functionality of PI3K in the control of cell motility, catalytic and non-catalytic, arising distinctly from juxtaposed regions within iSH2.

CLIP: accurate prediction of disordered linear interacting peptides from protein sequences using co-evolutionary information

One of key features of intrinsically disordered regions (IDRs) is facilitation of protein-protein and protein-nucleic acids interactions. These disordered binding regions include molecular recognition features (MoRFs), short linear motifs (SLiMs) and longer binding domains. Vast majority of current predictors of disordered binding regions target MoRFs, with a handful of methods that predict SLiMs and disordered protein-binding domains. A new and broader class of disordered binding regions, linear interacting peptides (LIPs), was introduced recently and applied in the MobiDB resource. LIPs are segments in protein sequences that undergo disorder-to-order transition upon binding to a protein or a nucleic acid, and they cover MoRFs, SLiMs and disordered protein-binding domains. Although current predictors of MoRFs and disordered protein-binding regions could be used to identify some LIPs, there are no dedicated sequence-based predictors of LIPs. To this end, we introduce CLIP, a new predictor of LIPs that utilizes robust logistic regression model to combine three complementary types of inputs: co-evolutionary information derived from multiple sequence alignments, physicochemical profiles and disorder predictions. Ablation analysis suggests that the co-evolutionary information is particularly useful for this prediction and that combining the three inputs provides substantial improvements when compared to using these inputs individually. Comparative empirical assessments using low-similarity test datasets reveal that CLIP secures area under receiver operating characteristic curve (AUC) of 0.8 and substantially improves over the results produced by the closest current tools that predict MoRFs and disordered protein-binding regions. The webserver of CLIP is freely available at http://biomine.cs.vcu.edu/servers/CLIP/ and the standalone code can be downloaded from http://yanglab.qd.sdu.edu.cn/download/CLIP/.

VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants

Determining the pathogenicity and functional impact (i.e. gain-of-function; GOF or loss-of-function; LOF) of a variant is vital for unraveling the genetic level mechanisms of human diseases. To provide a 'one-stop' framework for the accurate identification of pathogenicity and functional impact of variants, we developed a two-stage deep-learning-based computational solution, termed VPatho, which was trained using a total of 9619 pathogenic GOF/LOF and 138 026 neutral variants curated from various databases. A total number of 138 variant-level, 262 protein-level and 103 genome-level features were extracted for constructing the models of VPatho. The development of VPatho consists of two stages: (i) a random under-sampling multi-scale residual neural network (ResNet) with a newly defined weighted-loss function (RUS-Wg-MSResNet) was proposed to predict variants' pathogenicity on the gnomAD_NV + GOF/LOF dataset; and (ii) an XGBOD model was constructed to predict the functional impact of the given variants. Benchmarking experiments demonstrated that RUS-Wg-MSResNet achieved the highest prediction performance with the weights calculated based on the ratios of neutral versus pathogenic variants. Independent tests showed that both RUS-Wg-MSResNet and XGBOD achieved outstanding performance. Moreover, assessed using variants from the CAGI6 competition, RUS-Wg-MSResNet achieved superior performance compared to state-of-the-art predictors. The fine-trained XGBOD models were further used to blind test the whole LOF data downloaded from gnomAD and accordingly, we identified 31 nonLOF variants that were previously labeled as LOF/uncertain variants. As an implementation of the developed approach, a webserver of VPatho is made publicly available at http://csbio.njust.edu.cn/bioinf/vpatho/ to facilitate community-wide efforts for profiling and prioritizing the query variants with respect to their pathogenicity and functional impact.

Expression of glycerol-3-phosphate acyltransferase increases non-polar lipid accumulation in Nannochloropsis oceanica

Microalgae are considered a suitable production platform for high-value lipids and oleochemicals. Several species including Nannochloropsis oceanica produce large amounts of essential [Formula: see text]-3 polyunsaturated fatty acids (PUFAs) which are integral components of food and feed and have been associated with health-promoting effects. N. oceanica can further accumulate high contents of non-polar lipids with chemical properties that render them a potential replacement for plant oils such as palm oil. However, biomass and lipid productivities obtained with microalgae need to be improved to reach commercial feasibility. Genetic engineering can improve biomass and lipid productivities, for instance by increasing carbon flux to lipids. Here, we report the overexpression of glycerol-3-phosphate acyltransferase (GPAT) in N. oceanica during favorable growth conditions as a strategy to increase non-polar lipid content. Transformants overproducing either an endogenous (NoGPAT) or a heterologous (Acutodesmus obliquus GPAT) GPAT enzyme targeted to the endoplasmic reticulum had up to 42% and 51% increased non-polar lipid contents, respectively, compared to the wild type. Biomass productivities of transformant strains were not substantially impaired, resulting in lipid productivities that were increased by up to 37% and 42% for NoGPAT and AoGPAT transformants, respectively. When exposed to nutrient stress, transformants and wild type had similar lipid contents, suggesting that GPAT enzyme exerts strong flux control on lipid synthesis in N. oceanica under favorable growth conditions. NoGPAT transformants further accumulated PUFAs in non-polar lipids, reaching a total of 6.8% PUFAs per biomass, an increase of 24% relative to the wild type. Overall, our results indicate that GPAT is an interesting target for engineering of lipid metabolism in microalgae, in order to improve non-polar lipid and PUFAs accumulation in microalgae.

Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling

The cardiac sarcomere is a cellular structure in the heart that enables muscle cells to contract. Dozens of proteins belong to the cardiac sarcomere, which work in tandem to generate force and adapt to demands on cardiac output. Intriguingly, the majority of these proteins have significant intrinsic disorder that contributes to their functions, yet the biophysics of these intrinsically disordered regions (IDRs) have been characterized in limited detail. In this review, we first enumerate these myofilament-associated proteins with intrinsic disorder (MAPIDs) and recent biophysical studies to characterize their IDRs. We secondly summarize the biophysics governing IDR properties and the state-of-the-art in computational tools toward MAPID identification and characterization of their conformation ensembles. We conclude with an overview of future computational approaches toward broadening the understanding of intrinsic disorder in the cardiac sarcomere.

Similar evolutionary trajectories in an environmental Cryptococcus neoformans isolate after human and murine infection

A pet cockatoo was the suspected source of Cryptococcus neoformans recovered from an immunocompromised patient with cryptococcosis based on molecular analyses available in 2000. Here, we report whole genome sequence analysis of the clinical and cockatoo strains. Both are closely related MATα strains belonging to the VNII lineage, confirming that the human infection likely originated from pet bird exposure. The two strains differ by 61 single nucleotide polymorphisms, including eight nonsynonymous changes involving seven genes. To ascertain whether changes in these genes are selected for during mammalian infection, we passaged the cockatoo strain in mice. Remarkably, isolates obtained from mouse tissue possess a frameshift mutation in one of the seven genes altered in the human sample (LQVO5_000317), a gene predicted to encode an SWI-SNF chromatin-remodeling complex protein. In addition, both cockatoo and patient strains as well as mouse-passaged isolates obtained from brain tissue had a premature stop codon in a homologue of ZFC3 (LQVO5_004463), a predicted single-zinc finger containing protein, which is associated with larger capsules when deleted and reverted to a full-length protein in the mouse-passaged isolates obtained from lung tissue. The patient strain and mouse-passaged isolates show variability in virulence factors, with differences in capsule size, melanization, rates of nonlytic expulsion from macrophages, and amoeba predation resistance. Our results establish that environmental strains undergo genomic and phenotypic changes during mammalian passage, suggesting that animal virulence can be a mechanism for genetic change and that the genomes of clinical isolates may provide a readout of mutations acquired during infection.

Self-Assembly of Tunable Intrinsically Disordered Peptide Amphiphiles

Intrinsically disordered peptide amphiphiles (IDPAs) present a novel class of synthetic conjugates that consist of short hydrophilic polypeptides anchored to hydrocarbon chains. These hybrid polymer-lipid block constructs spontaneously self-assemble into dispersed nanoscopic aggregates or ordered mesophases in aqueous solution due to hydrophobic interactions. Yet, the possible sequence variations and their influence on the self-assembly structures are vast and have hardly been explored. Here, we measure the nanoscopic self-assembled structures of four IDPA systems that differ by their amino acid sequence. We show that permutations in the charge pattern along the sequence remarkably alter the headgroup conformation and consequently alter the pH-triggered phase transitions between spherical, cylindrical micelles and hexagonal condensed phases. We demonstrate that even a single amino acid mutation is sufficient to tune structural transitions in the condensed IDPA mesophases, while peptide conformations remain unfolded and disordered. Furthermore, alteration of the peptide sequence can render IDPAs to become susceptible to enzymatic cleavage and induce enzymatically activated phase transitions. These results hold great potential for embedding multiple functionalities into lipid nanoparticle delivery systems by incorporating IDPAs with the desired properties.

HSP70-binding motifs function as protein quality control degrons

Protein quality control (PQC) degrons are short protein segments that target misfolded proteins for proteasomal degradation, and thus protect cells against the accumulation of potentially toxic non-native proteins. Studies have shown that PQC degrons are hydrophobic and rarely contain negatively charged residues, features which are shared with chaperone-binding regions. Here we explore the notion that chaperone-binding regions may function as PQC degrons. When directly tested, we found that a canonical Hsp70-binding motif (the APPY peptide) functioned as a dose-dependent PQC degron both in yeast and in human cells. In yeast, Hsp70, Hsp110, Fes1, and the E3 Ubr1 target the APPY degron. Screening revealed that the sequence space within the chaperone-binding region of APPY that is compatible with degron function is vast. We find that the number of exposed Hsp70-binding sites in the yeast proteome correlates with a reduced protein abundance and half-life. Our results suggest that when protein folding fails, chaperone-binding sites may operate as PQC degrons, and that the sequence properties leading to PQC-linked degradation therefore overlap with those of chaperone binding.

DeepPRObind: Modular Deep Learner that Accurately Predicts Structure and Disorder-Annotated Protein Binding Residues

Current sequence-based predictors of protein-binding residues (PBRs) belong to two distinct categories: structure-trained vs. intrinsic disorder-trained. Since disordered PBRs differ from structured PBRs in several ways, including ability to bind multiple partners by folding into different conformations and enrichment in different amino acids, the structure-trained and disorder-trained predictors were shown to provide inaccurate results for the other annotation type. A simple consensus-based solution that combines structure- and disorder-trained methods provides limited levels of predictive performance and generates relatively many cross-predictions, where residues that interact with other ligand types are predicted as PBRs. We address this unsolved problem by designing a novel and fast deep-learner, DeepPRObind, that relies on carefully designed modular convolutional architecture and uses innovative aggregate input features. Comparative empirical tests on a low-similarity test dataset reveal that DeepPRObind generates accurate predictions of structured and disordered PBRs and low amounts of cross-predictions, outperforming a comprehensive collection of 12 predictors of PBRs. Given the relatively low runtime of DeepPRObind (40 seconds per protein), we further validate its results based on an analysis of putative PBRs in the yeast proteome, confirming that interactions in disordered regions are enriched among hub proteins. We release DeepPRObind as a convenient web server at https://www.csuligroup.com/DeepPRObind/.

The Chromatin Regulator HMGA1a Undergoes Phase Separation in the Nucleus

The protein high mobility group A1 (HMGA1) is an important regulator of chromatin organization and function. However, the mechanisms by which it exerts its biological function are not fully understood. Here, we report that the HMGA isoform, HMGA1a, nucleates into foci that display liquid-like properties in the nucleus, and that the protein readily undergoes phase separation to form liquid condensates in vitro. By bringing together machine-leaning modelling, cellular and biophysical experiments and multiscale simulations, we demonstrate that phase separation of HMGA1a is promoted by protein-DNA interactions, and has the potential to be modulated by post-transcriptional effects such as phosphorylation. We further show that the intrinsically disordered C-terminal tail of HMGA1a significantly contributes to its phase separation through electrostatic interactions via AT hooks 2 and 3. Our work sheds light on HMGA1 phase separation as an emergent biophysical factor in regulating chromatin structure.

Evolution of the orthopoxvirus core genome

Orthopoxviruses comprise several relevant pathogens, including the causative agent of smallpox and monkeypox virus. Analysis of orthopoxvirus genome evolution mainly focused on gene gains/losses. We instead analyzed core genes, which are conserved in all orthopoxviruses. We show that, despite their strong constraint, some genes involved in viral morphogenesis and transcription/replication were targets of pervasive positive selection, which was relatively uncommon in immunomodulatory genes. However at least three of the positively selected genes, E3L, A24R, and H3L, might have evolved in response to immune selection. Episodic positive selection was particularly common on the internal branches of the orthopox phylogeny and on the monkeypox virus lineage. The latter showed evidence of episodic positive selection at the D14L gene, which encodes a modulator of complement activation (MOPICE). Notably, two genes (B1R and A33R) targeted by episodic selection on more than one branch are involved in forms of intra-genomic conflict. Finally, we found that, in orthopoxvirus proteomes, intrinsically disordered regions (IDRs) tend to be less constrained and are common targets of positive selection. Extension of our analysis to all poxviruses showed no evidence that the IDR fraction differs with host range. Conversely, we found a strong effect of base composition, which was however not sufficient to explain IDR fraction. We thus suggest that, in poxviruses, the IDR fraction is maintained by modulating GC content to accommodate disorder-promoting codons. Overall, our data provide novel insight in orthopoxvirus evolution and provide a list of genes and sites that are expected to modulate viral phenotypes.

Non-catalytic role of phosphoinositide 3-kinase in mesenchymal cell migration through non-canonical induction of p85β/AP-2-mediated endocytosis

Class IA phosphoinositide 3-kinase (PI3K) galvanizes fundamental cellular processes such as migration, proliferation, and differentiation. To enable multifaceted roles, the catalytic subunit p110 utilizes a multidomain, regulatory subunit p85 through its inter SH2 domain (iSH2). In cell migration, their product PI(3,4,5)P3 generates locomotive activity. While non-catalytic roles are also implicated, underlying mechanisms and its relationship to PI(3,4,5)P3 signaling remain elusive. Here, we report that a disordered region of iSH2 contains previously uncharacterized AP-2 binding motifs which can trigger clathrin and dynamin-mediated endocytosis independent of PI3K catalytic activity. The AP-2 binding motif mutants of p85 aberrantly accumulate at focal adhesions and upregulate both velocity and persistency in fibroblast migration. We thus propose the dual functionality of PI3K in the control of cell motility, catalytic and non-catalytic, arising distinctly from juxtaposed regions within iSH2.

Computational Methods to Predict Intrinsically Disordered Regions and Functional Regions in Them

Intrinsically disordered regions (IDRs) are protein regions that do not adopt fixed tertiary structures. Since these regions lack ordered three-dimensional structures, they should be excluded from the target portions of homology modeling. IDRs can be predicted from the amino acid sequences, because their amino acid compositions are different from that of the structured domains. This chapter provides a review of the prediction methods of IDRs and a case study of IDR prediction.

Approaches for the Identification of Intrinsically Disordered Protein Domains

Intrinsically disordered protein domains are those with high disorder proportion or a consecutive disordered region. They have no stable spatial structure but play an important role in the regulation of complex cellular functions and contribute to the increasing organism complexity during evolution. Here, we describe the approaches to predict intrinsic disorder values of residues in proteins and methods to identify the intrinsically disordered domains.

Prediction of effector protein structures from fungal phytopathogens enables evolutionary analyses

Elucidating the similarity and diversity of pathogen effectors is critical to understand their evolution across fungal phytopathogens. However, rapid divergence that diminishes sequence similarities between putatively homologous effectors has largely concealed the roots of effector evolution. Here we modelled the structures of 26,653 secreted proteins from 14 agriculturally important fungal phytopathogens, six non-pathogenic fungi and one oomycete with AlphaFold 2. With 18,000 successfully predicted folds, we performed structure-guided comparative analyses on two aspects of effector evolution: uniquely expanded sequence-unrelated structurally similar (SUSS) effector families and common folds present across the fungal species. Extreme expansion of lineage-specific SUSS effector families was found only in several obligate biotrophs, Blumeria graminis and Puccinia graminis. The highly expanded effector families were the source of conserved sequence motifs, such as the Y/F/WxC motif. We identified new classes of SUSS effector families that include known virulence factors, such as AvrSr35, AvrSr50 and Tin2. Structural comparisons revealed that the expanded structural folds further diversify through domain duplications and fusion with disordered stretches. Putatively sub- and neo-functionalized SUSS effectors could reconverge on regulation, expanding the functional pools of effectors in the pathogen infection cycle. We also found evidence that many effector families could have originated from ancestral folds conserved across fungi. Collectively, our study highlights diverse effector evolution mechanisms and supports divergent evolution as a major force in driving SUSS effector evolution from ancestral proteins.

Easy Not Easy: Comparative Modeling with High-Sequence Identity Templates

Homology modeling is the most common technique to build structural models of a target protein based on the structure of proteins with high-sequence identity and available high-resolution structures. This technique is based on the idea that protein structure shows fewer changes than sequence through evolution. While in this scenario single mutations would minimally perturb the structure, experimental evidence shows otherwise: proteins with high conformational diversity impose a limit of the paradigm of comparative modeling as the same protein sequence can adopt dissimilar three-dimensional structures. These cases present challenges for modeling; at first glance, they may seem to be easy cases, but they have a complexity that is not evident at the sequence level. In this chapter, we address the following questions: Why should we care about conformational diversity? How to consider conformational diversity when doing template-based modeling in a practical way?

Identification of Phase Separating Proteins With Distributed Reduced Alphabet Representations of Sequences

Phase separation of proteins play key roles in cellular physiology including bacterial division, tumorigenesis etc. Consequently, understanding the molecular forces that drive phase separation has gained considerable attention and several factors including hydrophobicity, protein dynamics, etc., have been implicated in phase separation. Data-driven identification of new phase separating proteins can enable in-depth understanding of cellular physiology and may pave way towards developing novel methods of tackling disease progression. In this work, we exploit the existing wealth of data on phase separating proteins to develop sequence-based machine learning method for prediction of phase separating proteins. We use reduced alphabet schemes based on hydrophobicity and conformational similarity along with distributed representation of protein sequences and biochemical properties as input features to Support Vector Machine (SVM) and Random Forest (RF) machine learning algorithms. We used both curated and balanced dataset for building the models. RF trained on balanced dataset with hydropathy, conformational similarity embeddings and biochemical properties achieved accuracy of 97%. Our work highlights the use of conformational similarity, a feature that reflects amino acid flexibility, and hydrophobicity for predicting phase separating proteins. Use of such "interpretable" features obtained from the ever-growing knowledgebase of phase separation is likely to improve prediction performances further.

DisCanVis: Visualizing integrated structural and functional annotations to better understand the effect of cancer mutations located within disordered proteins

Intrinsically disordered proteins (IDPs) play important roles in a wide range of biological processes and have been associated with various diseases, including cancer. In the last few years, cancer genome projects have systematically collected genetic variations underlying multiple cancer types. In parallel, the number and different types of disordered proteins characterized by experimental methods have also significantly increased. Nevertheless, the role of IDPs in various types of cancer is still not well understood. In this work, we present DisCanVis, a novel visualization tool for cancer mutations with a special focus on IDPs. In order to aid the interpretation of observed mutations, genome level information is combined with information about the structural and functional properties of proteins. The web server enables users to inspect individual proteins, collect examples with existing annotations of protein disorder and associated function or to discover currently uncharacterized examples with likely disease relevance. Through a REST API interface and precompiled tables the analysis can be extended to a group of proteins.

Modelling the Transitioning of SARS-CoV-2 nsp3 and nsp4 Lumenal Regions towards a More Stable State on Complex Formation

During coronavirus infection, three non-structural proteins, nsp3, nsp4, and nsp6, are of great importance as they induce the formation of double-membrane vesicles where the replication and transcription of viral gRNA takes place, and the interaction of nsp3 and nsp4 lumenal regions triggers membrane pairing. However, their structural states are not well-understood. We investigated the interactions between nsp3 and nsp4 by predicting the structures of their lumenal regions individually and in complex using AlphaFold2 as implemented in ColabFold. The ColabFold prediction accuracy of the nsp3-nsp4 complex was increased compared to nsp3 alone and nsp4 alone. All cysteine residues in both lumenal regions were modelled to be involved in intramolecular disulphide bonds. A linker region in the nsp4 lumenal region emerged as crucial for the interaction, transitioning to a structured state when predicted in complex. The key interactions modelled between nsp3 and nsp4 appeared stable when the transmembrane regions of nsp3 and nsp4 were added to the modelling either alone or together. While molecular dynamics simulations (MD) demonstrated that the proposed model of the nsp3 lumenal region on its own is not stable, key interactions between nsp and nsp4 in the proposed complex model appeared stable after MD. Together, these observations suggest that the interaction is robust to different modelling conditions. Understanding the functional importance of the nsp4 linker region may have implications for the targeting of double membrane vesicle formation in controlling coronavirus infection.

Beyond sequence: Structure-based machine learning

Recent breakthroughs in protein structure prediction demarcate the start of a new era in structural bioinformatics. Combined with various advances in experimental structure determination and the uninterrupted pace at which new structures are published, this promises an age in which protein structure information is as prevalent and ubiquitous as sequence. Machine learning in protein bioinformatics has been dominated by sequence-based methods, but this is now changing to make use of the deluge of rich structural information as input. Machine learning methods making use of structures are scattered across literature and cover a number of different applications and scopes; while some try to address questions and tasks within a single protein family, others aim to capture characteristics across all available proteins. In this review, we look at the variety of structure-based machine learning approaches, how structures can be used as input, and typical applications of these approaches in protein biology. We also discuss current challenges and opportunities in this all-important and increasingly popular field.

Functional and structural characterization of an endo-β-1,3-glucanase from Euglena gracilis

Endo-β-1,3-glucanases from several organisms have attracted much attention in recent years because of their capability for in vitro degrading β-1,3-glucan as a critical step for both biofuels production and short-chain oligosaccharides synthesis. In this study, we biochemically characterized a putative endo-β-1,3-glucanase (EgrGH64) belonging to the family GH64 from the single-cell protist Euglena gracilis. The gene coding for the enzyme was heterologously expressed in a prokaryotic expression system supplemented with 3% (v/v) ethanol to optimize the recombinant protein right folding. Thus, the produced enzyme was highly purified by immobilized-metal affinity and gel filtration chromatography. The enzymatic study demonstrated that EgrGH64 could hydrolyze laminarin (K_M 23.5 mg ml^-1,k_cat 1.20 s^-1) and also, but with less enzymatic efficiency, paramylon (K_M 20.2 mg ml^-1,k_cat 0.23 ml mg^-1 s^-1). The major product of the hydrolysis of both substrates was laminaripentaose. The enzyme could also use ramified β-glucan from the baker's yeast cell wall as a substrate (K_M 2.10 mg ml^-1, k_cat 0.88 ml mg^-1 s^-1). This latter result, combined with interfacial kinetic analysis evidenced a protein's greater efficiency for the yeast polysaccharide, and a higher number of hydrolysis sites in the β-1,3/β-1,6-glucan. Concurrently, the enzyme efficiently inhibited the fungal growth when used at 1.0 mg/mL (15.4 μM). This study contributes to assigning a correct function and determining the enzymatic specificity of EgrGH64, which emerges as a relevant biotechnological tool for processing β-glucans.

PTMint database of experimentally verified PTM regulation on protein-protein interaction

MOTIVATION

Post-translational modification (PTM) is an important biochemical process. which includes six most well-studied types: phosphorylation, acetylation, methylation, sumoylation, ubiquitylation and glycosylation. PTM is involved in various cell signaling pathways and biological processes. Abnormal PTM status is closely associated with severe diseases (such as cancer and neurologic diseases) by regulating protein functions, such as protein-protein interactions (PPIs). A set of databases was constructed separately for PTM sites and PPI; however, the resource of regulation for PTM on PPI is still unsolved.

RESULTS

Here, we firstly constructed a public accessible database of PTMint (PTMs that are associated with PPIs) (https://ptmint.sjtu.edu.cn/) that contains manually curated complete experimental evidence of the PTM regulation on PPIs in multiple organisms, including Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Currently, the first version of PTMint encompassed 2477 non-redundant PTM sites in 1169 proteins affecting 2371 protein-protein pairs involving 357 diseases. Various annotations were systematically integrated, such as protein sequence, structure properties and protein complex analysis. PTMint database can help to insight into disease mechanism, disease diagnosis and drug discovery associated with PTM and PPI.

AVAILABILITY AND IMPLEMENTATION

PTMint is freely available at: https://ptmint.sjtu.edu.cn/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Biochemical and Biophysical Characterization of the Caveolin-2 Interaction with Membranes and Analysis of the Protein Structural Alteration by the Presence of Cholesterol

Caveolin-2 is a protein suitable for the study of interactions of caveolins with other proteins and lipids present in caveolar lipid rafts. Caveolin-2 has a lower tendency to associate with high molecular weight oligomers than caveolin-1, facilitating the study of its structural modulation upon association with other proteins or lipids. In this paper, we have successfully expressed and purified recombinant human caveolin-2 using E. coli. The structural changes of caveolin-2 upon interaction with a lipid bilayer of liposomes were characterized using bioinformatic prediction models, circular dichroism, differential scanning calorimetry, and fluorescence techniques. Our data support that caveolin-2 binds and alters cholesterol-rich domains in the membranes through a CARC domain, a type of cholesterol-interacting domain in its sequence. The far UV-CD spectra support that the purified protein keeps its folding properties but undergoes a change in its secondary structure in the presence of lipids that correlates with the acquisition of a more stable conformation, as shown by differential scanning calorimetry experiments. Fluorescence experiments using egg yolk lecithin large unilamellar vesicles loaded with 1,6-diphenylhexatriene confirmed that caveolin-2 adsorbs to the membrane but only penetrates the core of the phospholipid bilayer if vesicles are supplemented with 30% of cholesterol. Our study sheds light on the caveolin-2 interaction with lipids. In addition, we propose that purified recombinant caveolin-2 can provide a new tool to study protein-lipid interactions within caveolae.

Biomolecular condensates can both accelerate and suppress aggregation of α-synuclein

Biomolecular condensates present in cells can fundamentally affect the aggregation of amyloidogenic proteins and play a role in the regulation of this process. While liquid-liquid phase separation of amyloidogenic proteins by themselves can act as an alternative nucleation pathway, interaction of partly disordered aggregation-prone proteins with preexisting condensates that act as localization centers could be a far more general mechanism of altering their aggregation behavior. Here, we show that so-called host biomolecular condensates can both accelerate and slow down amyloid formation. We study the amyloidogenic protein α-synuclein and two truncated α-synuclein variants in the presence of three types of condensates composed of nonaggregating peptides, RNA, or ATP. Our results demonstrate that condensates can markedly speed up amyloid formation when proteins localize to their interface. However, condensates can also significantly suppress aggregation by sequestering and stabilizing amyloidogenic proteins, thereby providing living cells with a possible protection mechanism against amyloid formation.

Drosophila insulator proteins exhibit in vivo liquid-liquid phase separation properties

Drosophila insulator proteins and the cohesin subunit Rad21 coalesce in vivo to form liquid-droplet condensates, suggesting that liquid–liquid phase separation mediates their function in 3D genome organization.

Mounting evidence implicates liquid–liquid phase separation (LLPS), the condensation of biomolecules into liquid-like droplets in the formation and dissolution of membraneless intracellular organelles (MLOs). Cells use MLOs or condensates for various biological processes, including emergency signaling and spatiotemporal control over steady-state biochemical reactions and heterochromatin formation. Insulator proteins are architectural elements involved in establishing independent domains of transcriptional activity within eukaryotic genomes. In Drosophila, insulator proteins form nuclear foci known as insulator bodies in response to osmotic stress. However, the mechanism through which insulator proteins assemble into bodies is yet to be investigated. Here, we identify signatures of LLPS by insulator bodies, including high disorder tendency in insulator proteins, scaffold–client–dependent assembly, extensive fusion behavior, sphericity, and sensitivity to 1,6-hexanediol. We also show that the cohesin subunit Rad21 is a component of insulator bodies, adding to the known insulator protein constituents and γH2Av. Our data suggest a concerted role of cohesin and insulator proteins in insulator body formation and under physiological conditions. We propose a mechanism whereby these architectural proteins modulate 3D genome organization through LLPS.

Assessing the Pathogenicity of In-Frame CACNA1F Indel Variants Using Structural Modeling

Small in-frame insertion-deletion (indel) variants are a common form of genomic variation whose impact on rare disease phenotypes has been understudied. The prediction of the pathogenicity of such variants remains challenging. X-linked incomplete congenital stationary night blindness type 2 (CSNB2) is a nonprogressive, inherited retinal disorder caused by variants in CACNA1F, encoding the Ca_v1.4α1 channel protein. Here, structural analysis was used through homology modeling to interpret 10 disease-correlated and 10 putatively benign CACNA1F in-frame indel variants. CSNB2-correlated changes were found to be more highly conserved compared with putative benign variants. Notably, all 10 disease-correlated variants but none of the benign changes were within modeled regions of the protein. Structural analysis revealed that disease-correlated variants are predicted to destabilize the structure and function of the Ca_v1.4α1 channel protein. Overall, the use of structural information to interpret the consequences of in-frame indel variants provides an important adjunct that can improve the diagnosis for individuals with CSNB2.

An in silico approach to study the role of epitope order in the multi-epitope-based peptide (MEBP) vaccine design

With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches, especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidates. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison and ranking for the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency (RMVP), MEBP vaccine potency (MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. Further, the MEBP variants with IDs, SPVC_446 and SPVC_537, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be preferred candidates for immediate experimental testing and validation. The method enables quicker selection and high throughput experimental validation of vaccine candidates. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time.

Construction of gene co-expression networks in cultured silkworm cells and identification of previously uncharacterized lepidopteran-specific genes required for chromosome dynamics

Advances in sequencing technology and bioinformatics have accelerated gene discovery and homology-based functional annotation in many species, and numerous targeted gene studies have greatly expanded the understanding of gene functions. Nevertheless, there are still many genes that lack homology with genes in other evolutionary lineages and are left as genes with unknown functions. We constructed a gene co-expression network from the Bombyx mori ovary-derived cell line, BmN4, and attempted to infer the biological roles of uncharacterized genes based on the correlation between the function-known and unknown genes. Within this network, we focused on the co-expression modules involved in chromosome architecture, dynamics, and integrity, and selected the uncharacterized genes for subsequent RNAi-based phenotypic screening. This approach enabled the identification of 5 genes whose knockdown led to abnormalities in chromosome dynamics and spindle morphology in mitosis. One of them was a recently characterized gene, BmCenp-T, which plays a central role in building the kinetochore protein complex on the silkworm holocentric chromosomes. In this study, we suggest a method for constructing the gene co-expression network and selecting candidate genes for small-scale RNAi screening. This approach is complementary to homology-based annotation and may be useful for the analysis of lineage-specific uncharacterized genes such as orphan genes.

Intrinsic Disorder as a Natural Preservative: High Levels of Intrinsic Disorder in Proteins Found in the 2600-Year-Old Human Brain

Proteomic analysis revealed the preservation of many proteins in the Heslington brain (which is at least 2600-year-old brain tissue uncovered within the skull excavated in 2008 from a pit in Heslington, Yorkshire, England). Five of these proteins-"main proteins": heavy, medium, and light neurofilament proteins (NFH, NFM, and NFL), glial fibrillary acidic protein (GFAP), and myelin basic (MBP) protein-are engaged in the formation of non-amyloid protein aggregates, such as intermediate filaments and myelin sheath. We used a wide spectrum of bioinformatics tools to evaluate the prevalence of functional disorder in several related sets of proteins, such as the main proteins and their 44 interactors, all other proteins identified in the Heslington brain, as well as the entire human proteome (20,317 manually curated proteins), and 10,611 brain proteins. These analyses revealed that all five main proteins, half of their interactors and almost one third of the Heslington brain proteins are expected to be mostly disordered. Furthermore, most of the remaining Heslington brain proteins are expected to contain sizable levels of disorder. This is contrary to the expected substantial (if not complete) elimination of the disordered proteins from the Heslington brain. Therefore, it seems that the intrinsic disorder of NFH, NFM, NFL, GFAP, and MBP, their interactors, and many other proteins might play a crucial role in preserving the Heslington brain by forming tightly folded brain protein aggregates, in which different parts are glued together via the disorder-to-order transitions.

Defining the characteristics of interferon-alpha-stimulated human genes: insight from expression data and machine learning

BACKGROUND

A virus-infected cell triggers a signalling cascade, resulting in the secretion of interferons (IFNs), which in turn induces the upregulation of the IFN-stimulated genes (ISGs) that play a role in antipathogen host defence. Here, we conducted analyses on large-scale data relating to evolutionary gene expression, sequence composition, and network properties to elucidate factors associated with the stimulation of human genes in response to IFN-α.

RESULTS

We find that ISGs are less evolutionary conserved than genes that are not significantly stimulated in IFN experiments (non-ISGs). ISGs show obvious depletion of GC content in the coding region. This influences the representation of some compositions following the translation process. IFN-repressed human genes (IRGs), downregulated genes in IFN experiments, can have similar properties to the ISGs. Additionally, we design a machine learning framework integrating the support vector machine and novel feature selection algorithm that achieves an area under the receiver operating characteristic curve (AUC) of 0.7455 for ISG prediction. Its application in other IFN systems suggests the similarity between the ISGs triggered by type I and III IFNs.

CONCLUSIONS

ISGs have some unique properties that make them different from the non-ISGs. The representation of some properties has a strong correlation with gene expression following IFN-α stimulation, which can be used as a predictive feature in machine learning. Our model predicts several genes as putative ISGs that so far have shown no significant differential expression when stimulated with IFN-α in the cell/tissue types in the available databases. A web server implementing our method is accessible at http://isgpre.cvr.gla.ac.uk/. The docker image at https://hub.docker.com/r/hchai01/isgpre can be downloaded to reproduce the prediction.